When working in a proof assistant, automation is key to discharging routine proof goals such as equations between algebraic expressions. Homotopy type theory allows the user to reason about higher structures, such as topological spaces, using higher inductive types (HITs) and univalence. Cubical type theory provides computational support for HITs and univalence. A difficulty when working in cubical type theory is dealing with the complex combinatorics of higher structures, an infinite-dimensional generalisation of equational reasoning. To solve these higher-dimensional equations consists in constructing cubes with specified boundaries. We develop a simplified cubical language in which we isolate and study two automation problems: contortion solving, where we attempt to "contort" a cube to fit a given boundary, and the more general Kan solving, where we search for solutions that involve pasting multiple cubes together. Both problems are difficult in the general case-Kan solving is even undecidable-so we focus on heuristics that perform well on practical examples. Our language encompasses different variations of cubical type theory which differ in their "contortion theory", i.e., the class of contortions they support. We provide a solver for the contortion problem for the most complex contortion theories currently being researched, the Dedekind and De Morgan contortions, by utilizing a reformulation of contortions in terms of poset maps. We solve Kan problems using constraint satisfaction programming, which is applicable independently of the underlying contortion theory. We have implemented our algorithms in an experimental Haskell solver that can be used to automatically solve many goals a user of cubical type theory might face. We illustrate this with a case study establishing the Eckmann-Hilton theorem using our solver, as well as various benchmarks.

We construct a linear type system inside dependent type theory. For this, we equip the output type of a program with a bag containing copies of each of the input variables. We call the number of copies of an input variable its multiplicity. We then characterise a dependent type which ensures that a program uses exactly the given multiplicity of each input variable. While our system is not closed under linear function types, we can program in the resulting system in a practical way using usual dependent functions, which we demonstrate by constructing standard programs on lists such as folds, unfolds and sorting algorithms. Since our linear type system is deeply embedded in a functional language, we can moreover dynamically compute multiplicities, which allows us to capture that a program uses a varying number of copies of some input depending on the other inputs. We can thereby give precise types to many functional programs that cannot be typed in systems with static multiplicities.

Homotopy type theory is a logical setting based on Martin-Löf type theory in which one can perform geometric constructions and proofs in a synthetic way. Namely, types can be interpreted as spaces (up to continuous deformation) and proofs as homotopy invariant constructions. In this context, loop spaces of pointed connected groupoids provide a natural representation of groups, and any group can be obtained as the loop space of such a type, which is then called a delooping of the group. There are two main methods to construct the delooping of an arbitrary group G. The first one consists in describing it as a pointed higher inductive type, whereas the second one consists in taking the connected component of the principal G-torsor in the type of sets equipped with an action of G. We show here that, when a presentation is known for the group, simpler variants of those constructions can be used to build deloopings. The resulting types are more amenable to computations and lead to simpler meta-theoretic reasoning. We also investigate, in this context, an abstract construction for the Cayley graph of a generated group and show that it encodes the relations of the group. Most of the developments performed in the article have been formalized using the cubical version of the Agda proof assistant.

Elfe is an interactive system for teaching basic proof methods in discrete mathematics. The user inputs a mathematical text written in fair English which is converted to a special data-structure of first-order formulas. Certain proof obligations implied by this intermediate representation are checked by automated theorem provers which try to either prove the obligations or find countermodels if an obligation is wrong. The result of the verification process is then returned to the user. Elfe is implemented in Haskell and can be accessed via a reactive web interface or from the command line. Background libraries for sets, relations and functions have been developed. It has been tested by students in the beginning of their mathematical studies.